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At least 505 records · Page 28

Evaluating Possible Formation Mechanisms of Criegee Intermediates during the Heterogeneous Autoxidation of Squalene

Organic molecules in the environment oxidatively degrade by a variety of free radical, microbial, and biogeochemical pathways. A significant pathway is heterogeneous autoxidation, in which degradation occurs via a network of carbon and oxygen centered free radicals. Recently, we found evidence for a new heterogeneous autoxidation mechanism of squalene that is initiated by hydroxyl (OH) radical addition to a carbon–carbon double bond and apparently propagated through pathways involving Criegee Intermediates (CI) produced from β-hydroxy peroxy radicals (β-OH-RO 2 •). It remains unclear, however, exactly how CI are formed from β-OH-RO 2 •, which could occur by a unimolecular or bimolecular pathway. Combining kinetic models and multiphase OH oxidation measurements of squalene, we evaluate the kinetic viability of three mechanistic scenarios. Scenario 1 assumes that CI are formed by the unimolecular bond scission of β-OH-RO 2 •, whereas Scenarios 2 and 3 test bimolecular pathways of β-OH-RO 2 • to yield CI. Scenario 1 best replicates the entire experimental data set, which includes effective uptake coefficients vs [OH] as well as the formation kinetics of the major products (i.e., aldehydes and secondary ozonides). Finally, although the unimolecular pathway appears to be kinetically viable, future high-level theory is needed to fully explain the mechanistic relationship between CI and β-OH-RO 2 • in the condensed phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature Homogeneity under Selective and Localized Microwave Heating in Structured Flow Reactors

Selective heating of different phases of multiphase systems via microwaves can result in energy savings and suppression of side reactions. However, materials properties and operating conditions that maximize temperature gradients are poorly understood. Here we utilize computational fluid dynamics (CFD) computations and temperature measurements in structured flow reactors (monoliths) in a monomodal microwave cavity to assess the temperature difference between the walls and the fluid and develop a simple lumped model to estimate when temperature gradients exist. We also explore the material’s thermal and electrical properties of structured reactors for isothermal catalyst conditions. We propose that CFD simulations can be used as a nonintrusive, predictive tool of temperature homogeneity. Importantly, we demonstrate that localized heating in the bed under several conditions rather than selective heating is responsible for the selectivity enhancement. Furthermore, our results indicate that structured beds made of high thermal conductivity materials avoid arcing and enable temperature homogeneity and low electrical conductivity materials allow microwaves to penetrate the domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Situ High-Temperature Synchrotron Diffraction Studies of (Fe,Cr,Al) 3 O 4 Spinels

The modeling of a loss-of-coolant-accident scenario involving nuclear fuels with FeCrAl cladding materials in consideration to replace a Zircaloy requires knowledge of the thermodynamics of oxidized structures. At temperatures higher than 1500 degrees C, oxidation of FeCrAl alloys forms (Fe,Cr,Al) 3 O 4 spinels. In situ high-energy X-ray diffraction in a conical nozzle levitator installed at beamline 6-ID-D of the APS was used to study the structural evolution of the oxides as a function of the temperature. Single-phase (spinel) and multiphase (spinel-corundum-FeAlO 3 ) regions are mapped as a function of the temperature for three different compositions of FeCrAl oxidation products. The thermal expansion coefficients and cation distribution in the spinel structure have been refined. The temperature at which complete melting of the fuel cladding is expected has been determined by the liquidus temperatures of the oxidized products to be between 1657 and 1834 degrees C in a 20% O 2 /Ar atmosphere using the cooling trace method. The liquidus temperature increases with increasing Al and Cr content in the spinel phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model

We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Kinetic Model for Predicting Trace Gas Uptake and Reaction

A model is developed to describe trace gas uptake and reaction with applications to aerosols and microdroplets. Gas uptake by the liquid is formulated as a coupled equilibria that links gas, surface, and bulk regions of the droplet or solution. Previously, this framework was used in explicit stochastic reaction-diffusion simulations to predict the reactive uptake kinetics of ozone with droplets containing aqueous aconitic acid, maleic acid, and sodium nitrite. With the use of prior data and simulation results, a new equation for the uptake coefficient is derived, which accounts for both surface and bulk reactions. Lambert W functions are used to obtain closed form solutions to the integrated rate laws for the multiphase kinetics; similar to previous expressions that describe Michaelis-Menten enzyme kinetics. Together these equations couple interface and bulk processes over a wide range of conditions and do not require many of the limiting assumptions needed to apply resistor model formulations to explain trace gas uptake and reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distinguishing Surface and Bulk Reactivity: Concentration-Dependent Kinetics of Iodide Oxidation by Ozone in Microdroplets

Iodine oxidation reactions play an important role in environmental, biological, and industrial contexts. The multiphase reaction between aqueous iodide and ozone is of particular interest due to its prevalence in the marine atmosphere and unique reactivity at the air–water interface. Here, we explore the concentration dependence of the I – + O 3 reaction in levitated microdroplets under both acidic and basic conditions. To interpret the experimental kinetics, molecular simulations are used to benchmark a kinetic model, which enables insight into the reactivity of the interface, the nanometer-scale subsurface region, and the bulk interior of the droplet. For all experiments, a kinetic description of gas- and liquid-phase diffusion is critical to interpreting the results. We find that the surface dominates the iodide oxidation kinetics under concentrated and acidic conditions, with the reactive uptake coefficient approaching an upper limit of 10 –2 at pH 3. In contrast, reactions in the subsurface dominate under more dilute and alkaline conditions, with inhibition of the surface reaction at pH 12 and an uptake coefficient that is 10× smaller. In conclusion, the origin of a changing surface mechanism with pH is explored and compared to previous ozone-dependent measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modified Winterbottom Construction Including Boundaries

There has been extensive work on the equilibrium shape of isolated nanoparticles with internal boundaries, and also single crystals on substrates. Surprisingly, almost shockingly, there has been very little work on the equilibrium shape of particles with internal boundaries on substrates. Here in this paper, the general solution is given for the configuration of particles which contain twin and other grain boundaries on a flat substrate, which can be applied to any polycrystalline or multiphase nanoparticle configuration. The solution is based upon combining the established modified-Wulff construction that has been extensively validated for twinned particles with the Winterbottom construction for single particles on a substrate. The solution is illustrated for the specific case of five-fold multiply twinned particles. Good agreement is observed between both existing experimental data in the literature as well as some experimental data included within this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Resolution Imaging of Unstained Polymer Materials

Electron microscopy has played an important role in polymer characterization. Traditionally, electron diffraction is used to study crystalline polymers while transmission electron microscopy is used to study microphase separation in stained block copolymers and other multiphase systems. We describe developments that eliminate the barrier between these two approaches - it is now possible to image polymer crystals with atomic resolution. The focus of this Review is on high-resolution imaging (30 Å and smaller) of unstained polymers. Recent advances in hardware allow for capturing numerous (as many as 105) low-dose images from an unperturbed specimen; beam damage is a significant barrier to high-resolution electron microscopy of polymers. Machine-learning-based software is then used to sort and average the images to retrieve pristine structural information from a collection of noisy images. Acknowledging the heterogeneity in polymer samples prior to averaging is essential. Molecular conformations in a wide range of amphiphilic block copolymers, polymerized ionic liquids, and conjugated polymers can be gleaned from two-dimensional projections (2D), three-dimensional (3D) tomograms, and four-dimensional (4D) scanning transmission electron microscopy (STEM) data sets where 2D diffraction patterns are taken as a function of position. Some methods such as phase contrast STEM have been used to image closely related materials such as metal-organic frameworks but not polymers. With improvements in hardware and software, such methods may soon be applied to polymers. Our goal is to provide a comprehensive understanding of the strategies toward the high-resolution imaging of radiation sensitive polymer materials at different length scales.

36 MATERIALS SCIENCE↗

Mechanistic Insights into Aldehyde Production from Electrochemical CO 2 Reduction on CuAg Alloy via Operando X-ray Measurements

CO 2 electrolysis converts the greenhouse gas CO 2 into valuable fuels and chemicals, such as carbon monoxide, ethylene, ethanol, etc. Currently, Cu is the only known monometallic catalyst capable of producing multicarbon products from electrochemical CO 2 reduction reaction (eCO2RR), while the poor selectivity limits its further use. It has been found that introducing Ag atoms into the Cu lattice can modulate product preference. However, the synergistic effects between Cu and Ag, and thus, the catalytic performance, are strongly influenced by catalyst morphology, electrolyzer configuration, reaction conditions, etc. Operando measurements can provide explicit information on the catalyst dynamic variation during the reaction, but their operation and analysis are challenging. Herein, we prepared CuAg multiphase alloy catalysts by magnetron sputtering, which allowed for investigating the intrinsic interaction between Cu and Ag. eCO2RR performance exhibited an improved selectivity toward carbonyls at the expense of hydrogen and hydrocarbons. The partially alloyed Cu and Ag phases were confirmed by operando X-ray diffraction. By means of combining operando X-ray measurements and density functional theory (DFT) calculations, the preferred carbonyl production is attributed to the reduced electron density and compressive strain of Cu due to Ag incorporation, which leads to a deeper d-band center and therefore weakened intermediate adsorption and oxophilicity. In conclusion, this work provides evidence of the intrinsic structural and electronic interaction between Cu and Ag during eCO2RR. The obtained information will facilitate the design of bi/multi-phase metallic or alloy electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tight Coupling of Surface and In-Plant Biochemistry and Convection Governs Key Fine Particulate Components over the Amazon Rainforest

We report that throughout the troposphere over the Amazon rainforest, isoprene epoxydiol-secondary organic aerosols (IEPOX-SOA) are key components of submicrometer particle mass. IEPOX-SOA is thought to form by multiphase chemical pathways in the atmosphere, but using detailed model simulations, we show that these pathways are strongly inhibited by the solid particle phase state prevailing in the upper troposphere. We find that 2-methyltetrol gases formed by in-plant biochemical oxidation pathways, their partitioning to fine particles, and dissolution in cloud droplets can explain over 90% of IEPOX-SOA mass concentrations in the upper troposphere. In agreement with previous PM10 chiral measurements, our simulations indicate that plant biochemical processes are the dominant source of particulate 2-methyltetrols in the lower troposphere as well (>70%). Our results imply that in-plant biochemistry plays a central but previously unidentified role in aerosol processes and atmosphere-biosphere-climate interactions over the rainforest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observationally Constrained Modeling of the Reactive Uptake of Isoprene-Derived Epoxydiols under Elevated Relative Humidity and Varying Acidity of Seed Aerosol Conditions

Isoprene is the non-methane volatile organic compound (VOC) emitted in largest amounts to the atmosphere, and it is a significant source of secondary organic aerosol (SOA) mass. The uptake of isoprene oxidation products followed by multiphase chemistry in fine particles is the key pathway to form isoprene epoxydiol-derived SOA (IEPOX-SOA). However, many parameters that relate to diffusion and reaction of IEPOX in the particle phase remain uncertain, since reaction kinetics previously measured in bulk aqueous phase solutions might be different from atmospheric aerosols. Here, we use simultaneous environmental chamber measurements of multiple parameters governing IEPOX-SOA formation at timescales of ~hours: particle size distribution, composition, and volatility of IEPOX-SOA to constrain the key parameters governing IE-POX-SOA formation under humid (i.e., 50% relative humidity, RH) and varying seed aerosol acidity conditions. Reducing the 2-methyltetrol (tetrol) reaction rate constants by a factor of 4 brings the model predictions in agreement with the IEPOX-SOA measurements with acidified ammonium bisulfate seed aerosols. For less acidic ammonium sulfate aerosols both the organo-sulfate (OS) and tetrol reaction rate constants need to be reduced to bring model predictions closer to chamber observations. Using the measured non-volatile content of IEPOX-SOA we constrain the oligomerization timescale of 2-methyltetrols. We find that the oligomerization timescale is 4 hours with acidified seed aerosols, but a much longer time scale of 24 hours is needed for non-acidified seed aerosols, indicating that the aerosol acidity greatly affects the oligomerization rate of tetrols. Here we show that the actual kinetics of IEPOX-SOA formation rate on aerosol seeds consisting of both ammonium bisulfate and ammonium sulfate are a factor of 4~5 slower under 50-60% RH conditions compared to their application in previous models, which were based on bulk aqueous solution measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San↗

High-Entropy 2D Carbide MXenes: TiVNbMoC 3 and TiVCrMoC 3

Two-dimensional (2D) transition metal carbides and nitrides, known as MXenes, are a fast-growing family of 2D materials. MXenes 2D flakes have n + 1 (n = 1-4) atomic layers of transition metals interleaved by carbon/nitrogen layers, but to-date remain limited in composition to one or two transition metals. In this study, by implementing four transition metals, we report the synthesis of multi-principal-element high-entropy M 4 C 3 T x MXenes. Specifically, we introduce two high-entropy MXenes, TiVNbMoC 3 T x and TiVCrMoC 3 T x , as well as their precursor TiVNbMoAlC 3 and TiVCrMoAlC 3 high-entropy MAX phases. We used a combination of real and reciprocal space characterization (X-ray diffraction, X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, and scanning transmission electron microscopy) to establish the structure, phase purity, and equimolar distribution of the four transition metals in high-entropy MAX and MXene phases. We use first-principles calculations to compute the formation energies and explore synthesizability of these high-entropy MAX phases. We also show that when three transition metals are used instead of four, under similar synthesis conditions to those of the four-transition-metal MAX phase, two different MAX phases can be formed (i.e., no pure single-phase forms). This finding indicates the importance of configurational entropy in stabilizing the desired single-phase high-entropy MAX over multiphases of MAX, which is essential for the synthesis of phase-pure high-entropy MXenes. The synthesis of high-entropy MXenes significantly expands the compositional variety of the MXene family to further tune their properties, including electronic, magnetic, electrochemical, catalytic, high temperature stability, and mechanical behavior.

2D materials↗

Mechanistic Insight into Lignin Slow Pyrolysis by Linking Pyrolysis Chemistry and Carbon Material Properties

As a highly abundant renewable carbon source, lignin can be converted to a variety of advanced carbon materials with tailorable properties through slow pyrolysis. In this study, slow pyrolysis of kraft lignin, for the first time, was investigated with a commercial pyrolysis–gas chromatography–mass spectrometry (Py–GC–MS) system through evolved gas analysis-MS (EGA-MS) and heart-cutting-GC–MS (HC-GC–MS) analyses. These analyses allow recovery and examination of the multiphased gas products generated from thermal decomposition of lignin during slow pyrolysis at a controlled heating rate over a long time course, thus making it possible to link operation conditions, pyrolysis chemistry, and carbon material properties. The overall product distributions, including volatiles and solid products, were quantitatively tracked at different heating rates (2, 20, and 40 °C/min) and different temperature regions (100–200, 200–300, and 300–600 °C). Solid residues were further characterized using a suite of analytical tools, in correlation with the investigation of formation mechanisms of volatiles to reveal the reaction chemistry of lignin during slow pyrolysis and to determine the morphology, pore structure, and interfacial chemical properties. This study provides critical insights into the slow pyrolysis chemistry of lignin and the properties of the resulting carbon material. These results will facilitate a better design and control of the lignin slow pyrolysis process for synthesizing functional carbon materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

System-Level Optimization to Improve Biofuel Potential via Genetic Engineering and Hydrothermal Liquefaction

The economic success of biofuels and bioproducts depends on system-level optimization including biomass production and conversion. Hydrothermal liquefaction (HTL) can convert wet biomass such as microalgae into a biofuel intermediate (BFI) under elevated temperatures and pressure. An understanding of the impacts of biomass composition on BFI yield and quality can inform genetic engineering strategies in the improvement of biochemical composition for biofuel production. In this work, wild type cyanobacterium Synechocystis sp. PCC 6803 biomass was doped with various common cellular storage compounds in lab-scale HTL experiments. Doping with glycogen or polyhydroxybutyrate (PHB) significantly reduced BFI yields, while doping with triglycerides (TAG) or medium chain-length polyhydroxyalkanoate (mcl-PHA) increased BFI yield and quality. In light of these observations, a genetically engineered Synechocystis strain deficient in glycogen biosynthesis was cultivated to produce biomass for HTL, leading to a 17% increase in BFI yield. In addition, we built a multiphase component additivity (MCA) model that can predict BFI yield and quality with PHAs in the biomass. This work demonstrates an effective strategy to integrate strain development with downstream biomass conversion to maximize biofuel yield, with lessons applicable to microalgae as well as other biomass.

09 BIOMASS FUELS↗

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗

Coupled Time-Lapse Full-Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation

We describe a novel framework for estimating subsurface properties, such as rock permeability and porosity, from time-lapse observed seismic data by coupling full-waveform inversion (FWI), subsurface flow processes, and rock physics models. For the inverse modeling, we handle the back propagation of gradients by an intrusive automatic differentiation strategy that offers three levels of user control: (1) At the wave physics level, we adopted the discrete adjoint method in order to use our existing high-performance FWI code; (2) at the rock physics level, we used built-in automatic differentiation operators from the TensorFlow backend; (3) at the flow physics level, we implemented customized partial differential equation (PDE) operators for the multiphase flow equations. The three-level coupled inversion strategy strikes a good balance between computational efficiency and programming efforts, and when the gradients are chained together, it constitutes a coupled inverse system. Our numerical experiments demonstrate that the three-level coupled inverse problem is superior in terms of accuracy to a traditional decoupled inversion strategy. Additionally, our method is able to simultaneously invert for parameters in empirical relationships such as the rock physics models. Our proposed inverted model can be used for reservoir performance prediction and reservoir management/optimization purposes.

54 ENVIRONMENTAL SCIENCES↗